A Two-Stage Real-time Prediction Method for Multiplayer Shooting E-Sports

E-sports is an industry with a huge base and the number of people who pay attention to it continues to rise. The research results of E-sports prediction play an important role in many aspects. In the past game prediction algorithms, there are mainly three kinds: neural network algorithm, AdaBoost algorithm based on Naïve Bayesian (NB) classifier and decision tree algorithm. These three algorithms have their own advantages and disadvantages, but they cannot predict the match ranking in real time. Therefore, we propose a real-time prediction algorithm based on random forest model. This method is divided into two stages. In the first stage, the weights are trained to obtain the optimal model for the second stage. In the second stage, each influencing factor in the data set is corresponded to and transformed with the data items in the competition log. The accuracy of the prediction results and its change trend with time are observed. Finally, the model is evaluated. The results show that the accuracy of real-time prediction reaches 92.29%, which makes up for the shortage of real-time in traditional prediction algorithm

Allelic shift in cis-elements of the transcription factor RAP2.12 underlies adaptation associated with humidity in Arabidopsis thaliana

Populations of widespread species are usually geographically distributed through contrasting stresses, but underlying genetic mechanisms controlling this adaptation remain largely unknown. Here, we show that in Arabidopsis thaliana, allelic changes in the cis-regulatory elements, WT box and W box, in the promoter of a key transcription factor associated with oxygen sensing, RELATED TO AP 2.12 (RAP2.12), are responsible for differentially regulating tolerance to drought and flooding. These two cis-elements are regulated by different transcription factors that downstream of RAP2.12 results in differential accumulation of hypoxia-responsive transcripts. The evolution from one cis-element haplotype to the other is associated with the colonization of humid environments from arid habitats. This gene thus promotes both drought and flooding adaptation via an adaptive mechanism that diversifies its regulation through noncoding alleles

Quantitative Measurement of the Sustainable Water Resource Development System in China Inspired by Dissipative Structure Theory

In an attempt to ensure sustainable water resource development, this paper constructs a comprehensive scientific index evaluation system focused on the macro socio-economic-ecological environment. Inspired by the theory of dissipative structure, the sustainable development system of water resources is regarded as a complex and huge dissipative system. In order to effectively measure the coordinated development status and orderly evolution trend of the system, this paper uses the information entropy method to construct the measurement model of the water resources system and analyze its internal entropy flow changes. The empirical analysis of the water resources in China from 2007 to 2016 found that coordinated water resource subsystem development could achieve sustainable development, and that over the examined period, the sustainable water resource development system in China became more orderly and coordinated; therefore, the sustainable development aim is gradually being achieved

Policy-driven Data Sharing over Attribute-Based Encryption supporting Dual Membership

Attribute-Based Encryption (ABE) plays an important role in current secure data sharing through fine-grained customizable policies. However, the existing ABE schemes only support simple predicates, = and ≠, but cannot express a more general membership predicates, ∈ and ∉, in policies. The low expressivity of ABE will enlarge the ciphertext storage and reduce the communication efficiency. To overcome this problem, we propose an ABE supporting Dual Membership (DM-ABE). The core problem for implementing this scheme is how to use cryptographic methods to decide the membership between the verified element and the given set. In order to solve this problem, we design a cryptographic algorithm, called Secure Decision of Membership (SDM), based on aggregation functions. In this algorithm, any set can be aggregated into one cryptographic element, and the verified element and the given set can be converted into another cryptographic element in decision process. The membership between them can be decided by the above two cryptographic elements. Furthermore, we construct the DM-ABE by using SDM. Because of the good expressivity of our DM-ABE, we further propose a novel cryptographic data sharing framework by integrating DM-ABE and attribute-based access control to provide fine-grained access control and security protection for private data. In the security proof of DM-ABE, we prove that the DM-ABE satisfies the semantic security against chosen-plaintext attacks under the DBDHE assumption in the standard model through a unified way, considering both two encryption methods for ∈ and ∉ at the same time. Finally, we analyze our scheme in terms of time and space complexity, and compare it with some existing schemes. The results show that our DM-ABE has a better expressive ability on the boolean logic of general membership predicates, ∈ and ∉.Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Cyber Securit